Timely Wireless Flows With General Traffic Patterns: Capacity Region and Scheduling Algorithms

Most existing wireless networking solutions are best-effort and do not provide any delay guarantee required by important applications, such as mobile multimedia conferencing and real-time control of cyber-physical systems. Recently, Hou and Kumar provided a novel framework for analyzing and designing delay-guaranteed wireless networking solutions. While inspiring, their idle-time-based analysis applies only to flows with a special traffic pattern called the frame-synchronized setting. The problem remains largely open for general traffic patterns. This paper addresses this challenge by proposing a general framework that characterizes and achieves the complete delay-constrained capacity region with general traffic patterns in single-hop downlink access-point wireless networks. We first show that the timely wireless flow problem is fundamentally an infinite-horizon Markov decision process (MDP). Then, we judiciously combine different simplification methods to prove that the timely capacity region can be characterized by a finite-size convex polygon. This for the first time allows us to characterize the timely capacity region of wireless flows with general traffic patterns. We then design three scheduling policies to optimize network utility and/or support feasible timely throughput vectors for general traffic patterns. The first policy achieves the optimal network utility and supports any feasible timely throughput vector but suffers from the curse of dimensionality. The second and third policies are inspired by our MDP framework and are of much lower complexity. Simulation results show that both achieve near-optimal performance and outperform other existing alternatives.